Here are two arguments.
Inverse function theorem
Let $M'\subset S$ be the $n^2-1$ dimensional manifold of matrices of rank $n-1.$
Let $P'$ be the $n(n+1)/2-1$ dimensional manifold of positive semidefinite matrices of rank $n-1.$
Your claim implies that the multiplication map $\mu:O^-_n\times P'\to M'$ defined by $\mu(O,P)=OP$ is a homeomorphism - the inverse sends $A$ to $(O(A),O(A)^{-1}A).$ I claim that $\mu$ is a diffeomorphism.
Thus your map $O:M'\to O^-_n$ is smooth - it's the inverse of $\mu$ composed with the projection to the $O^-_n$ component.
The dimensions match: $n(n-1)/2+n(n+1)/2-1=n^2-1.$ So for the inverse function theorem to apply we only need to check that $d\mu$ is injective.
Tangent vectors to $O^-_n\times P'$ at $(O,P)$ are of the form $(OA,S)$ where $A$ is antisymmetric and $S$ is symmetric.
Assume that $d\mu_{(O,P)}(OA,S)$ is zero. So $OAP+OS=0.$ This means $AP$ is symmetric.
Let $x_1,\dots,x_n$ be an orthonormal basis of eigenvalues of $P$ with corresponding eigenvalues $\lambda_1,\dots,\lambda_n.$
For indices $i\neq j,$
$$\lambda_jx_i^TAx_j=x_i^TAPx_j=x_i^T(AP)^Tx_j=-x_i^TPAx_j=-\lambda_ix_i^TAx_j,$$
but $\lambda_j$ can't equal $-\lambda_i$ for $i\neq j,$ so $x_i^TAx_j=0.$
And $x_i^TAx_i=0$ because $A$ is antisymmetric. This implies that $A$ is zero, and $S$ must therefore also be zero.
So $d\mu$ is injective as required.
(If you wanted to show that $O$ is smooth on $S,$ in the manifold-with-boundary sense of all derivatives being continuous at each rank $n-1$ matrix, you could extend $P'$ to an open neighborhood such as the matrices with least eigenvalues $\lambda_1,\lambda_2$ satisfying $\lambda_1>-\lambda_2,$ use $\mathbb R^{n\times n}$ as the codomain for $\mu,$ and check it's still a local diffeo.)
Subtracting cofactor matrix
$\DeclareMathOperator{\cof}{cof}$
Let $\cof(A)$ denote the cofactor matrix of a matrix $A.$ The important properties are that $\cof$ is smooth (in fact algebraic) and $A \cdot \cof(A)^T=\det(A)I.$
If $U,V$ are orthogonal and $\Sigma$ is diagonal then
$$\cof(U\Sigma V^T)=\det(UV^T)U\cdot \cof(\Sigma) \cdot V^T$$
and $\cof(\Sigma)$ is diagonal with $i$'th diagonal entry $\det(UV^T)\prod_{j\neq i}\Sigma_{jj}.$
(To verify that this is correct, it suffices to check $A \cdot \cof(A)^T=\det(A)I$ with $A=U\Sigma V^T,$ because that characterizes $\cof(A)$ for non-singular $A,$ and for singular $A$ we can use continuity in $\Sigma$ with $U,V$ fixed.)
The relevant situation is when $A=U\Sigma V^T$ is an SVD, the rank is $n-1,$ and $\det(UV^T)=-1.$
With the convention that singular values are in descending order, $\Sigma_{nn}=0.$
Then $\cof(\Sigma)$ is zero except for its $nn$ entry which is $\prod_{1\leq j<n}\Sigma_{jj}>0.$
So $\Sigma-\det(UV^T)\cof(\Sigma)=\Sigma+\cof(\Sigma)$ is strictly positive definite.
This implies that $A-\cof(A)$ is a non-singular matrix with the correct orthogonal polar factor $O(A-\cof(A))=UV^T.$
$A\mapsto A-\cof(A)$ is smooth (in fact algebraic), and $O$ is smooth on non-singular matrices,
so the composition $A\mapsto O(A-\cof(A))$ is smooth and well-defined when restricted to rank $n-1$ matrices.
(If you wanted to show that $O$ is smooth on $S,$ in the manifold-with-boundary sense of all derivatives being continuous at each rank $n-1$ matrix, you could use the fact that $A-\cof(A)$ must be non-singular in a ball around a given $A$ of rank $n-1.$)